A live machine status board shows every machine running, under breakdown or idle — right now. Underneath, the same work orders build MTTR, MTBF and availability over time, downtime analysis and breakdown ageing, with maintenance and asset history reports beside them. Reliability stops being a feeling and becomes a chart you can put in front of management review.
The dashboards aren't a separate data-entry chore — they are the by-product of the work you already record. See where the numbers come from in our CMMS guide.
The live machine status board puts every machine's current state on one screen — running, under breakdown or idle — so a supervisor reads the floor without walking it. From the board you can open a machine to Start/Stop it, Report a Problem and pick a stoppage reason, so real-time state and the breakdown that caused it live in the same place. Filter by shift, area or operator and the picture narrows to exactly what you need to see.
The machine breakdown dashboard turns real work orders into the two numbers reliability lives by: MTTR — the average time to restore a machine after a breakdown — and MTBF, the average running time between failures. Both are plotted over time and machine-wise, so you see whether repairs are getting faster and machines are failing less. Pick a machine from the dropdown and its own MTTR and MTBF trend appears, no spreadsheet gymnastics required.
Reliability averages hide where the pain is. Downtime analysis breaks breakdown maintenance hours down by machine and by cause, so the handful of assets and failures eating your uptime stand out. Breakdown ageing shows how long open breakdowns have been running, so the oldest stoppages surface first and nothing quietly sits open for a week. It is the difference between "the plant was down a lot" and "these three machines, this one cause".
Around the KPIs sit the reports that make them useful: a maintenance history report, an asset history report and the maintenance calendar of scheduled and due PM. Email, SMS and WhatsApp alerts push breakdown, PM-due and reorder events to the right people. And Dhruv AI — the Fast Suite's own AI and BI layer — adds maintenance role dashboards, plain-English questions answered through a read-only query engine, and clustering of breakdown-cause remarks into recurring themes.
Every machine's current state — running, under breakdown or idle — on one screen, with Start/Stop and Report Problem from the board.
Mean time to repair, plotted over time and machine-wise from real breakdown work orders — is your team restoring machines faster?
Mean time between failures over time and per machine — is servicing on schedule actually making machines fail less often?
Uptime as a percentage, computed from running time and captured downtime, so availability sits beside MTTR and MTBF.
Breakdown maintenance hours broken down by machine and cause, so the worst offenders and recurring failures stand out.
How long open breakdowns have been running, oldest first, so nothing quietly sits open while the plant loses hours.
A maintenance history report and an asset history report, so every breakdown and PM against a machine reads back in one place.
Scheduled, due and overdue preventive work in a calendar view, so planned maintenance sits beside the reliability picture.
Email, SMS and WhatsApp alerts plus Dhruv AI role dashboards, plain-English queries and breakdown-cause clustering.
Reliability KPIs assembled by hand at month-end are always too late to act on. Here is what a live, work-order-driven board changes.
The live machine status board shows every machine's current state — running, under breakdown or idle — on one screen, updated as operators and supervisors start, stop and report problems against machines. From the board a supervisor can open a machine to start or stop it, report a problem and pick a stoppage reason, so the plant's real-time state and its breakdowns are visible in the same place.
MTTR (mean time to repair) is the average time taken to restore a machine after a breakdown; MTBF (mean time between failures) is the average running time between breakdowns. Fast Maintenance builds both from real breakdown work orders — the captured start–stop downtime and the intervals between failures — so the machine breakdown dashboard can plot MTTR over time, MTBF over time, and machine-wise versions of each.
Yes. The machine breakdown dashboard reports breakdown maintenance hours and downtime analysis, and breakdown ageing shows how long open breakdowns have been running so the oldest stoppages surface first. Together they turn a pile of individual breakdowns into a picture of which machines and which causes are costing the most uptime.
Beyond the live status board and the MTTR/MTBF charts, you get availability, downtime analysis, breakdown ageing, a maintenance history report and an asset history report, plus the maintenance calendar of scheduled and due preventive work. Because breakdown and preventive maintenance share one asset record, every KPI traces back to the machine and the work orders behind it.
Yes. Email, SMS and WhatsApp alerts push breakdown, PM-due and reorder events to the right people, and Dhruv AI — the Fast Suite's own AI and BI layer — adds maintenance role dashboards, plain-English questions answered through a read-only query engine, and clustering of breakdown-cause remarks into recurring themes. Fast Maintenance runs cloud or on-premise, for manufacturers of every kind, across India and worldwide.
Live demo of the machine status board, MTTR/MTBF trends and downtime analysis — on your own machines. Cloud or on-premise, no generic slideshow.
